Journal
BIOINFORMATICS
Volume 33, Issue 20, Pages 3166-3172Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btx401
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Funding
- Hong Kong University Grants Committee Hong Kong UGC/AoE Plant & Agricultural Biotechnology Project [AoE-B-07/09]
- Shenzhen Science and Technology Committee [JCYJ20140425184428456]
- Hong Kong Research Grants Council [CUHK400913]
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Motivation: Although high-throughput sequencing methods have been proposed to identify splicing branch points in the human genome, these methods can only detect a small fraction of the branch points subject to the sequencing depth, experimental cost and the expression level of the mRNA. An accurate computational model for branch point prediction is therefore an ongoing objective in human genome research. Results: We here propose a novel branch point prediction algorithm that utilizes information on the branch point sequence and the polypyrimidine tract. Using experimentally validated data, we demonstrate that our proposed method outperforms existing methods.
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